{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Interpreting ResNet CIFAR-10 Training Process With Forgetting Events"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook trains a ResNet model using CIFAR-10 dataset and employed Forgetting Events algorithm, specifically `ForgettingEventsInterpreter`, to investigate the training process. A **forgetting event** occurrs when an individual training example transitions from being classified correctly to incorrectly over the course of learning. Some examples are forgotten frequently while others are not. This will help us understand whilch training example is more helpful for generalization performaces."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import paddle\n",
    "import numpy as np\n",
    "from PIL import Image\n",
    "import matplotlib.pyplot as plt\n",
    "import interpretdl as it"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define the training dataset using the CIFAR10 dataset generator from **paddle.vision.datasets**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from paddle.vision.transforms import Transpose\n",
    "from paddle.vision.datasets import Cifar10\n",
    "\n",
    "train_dataset = Cifar10(mode='train', transform=Transpose())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Initialize the ResNet50 model using **paddle.vision.models**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from paddle.vision.models import resnet50\n",
    "model = resnet50(pretrained=False, num_classes=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up a data loader with batch size of 128, and an Momentum optimizer for training.\n",
    "\n",
    "**Note:** the data generator shoud be able to generate the index of each sample, the sample and its label, so that each sample's behavior can be recorded according to its index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def reader_prepare(dataset):\n",
    "    def reader():\n",
    "        counter_ = -1\n",
    "        for sample, label in dataset:\n",
    "            counter_ += 1\n",
    "            yield counter_, (sample / 255.0).astype(np.float32), int(label)\n",
    "\n",
    "    return reader\n",
    "\n",
    "BATCH_SIZE = 128\n",
    "train_reader = paddle.batch(\n",
    "    reader_prepare(train_dataset), batch_size=BATCH_SIZE)\n",
    "optimizer = paddle.optimizer.Momentum(learning_rate=0.001,\n",
    "                     momentum=0.9,\n",
    "                     parameters=model.parameters())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First initialize the `ForgettingEventsInterpreter` and then start `interpret`ing the training process by training 100 epochs. \n",
    "\n",
    "*stats* is a dictionary that maps image index to predictions in the training process and if they are correct; *count_forgotten* is a dictionary where its keys are number of fogotten times and values are a list of image indices with such number of fogotten times; *forgotten* is a dictionary that maps image index to an array of misclassified labels. They are saved at \"assets/stats.pkl\", \"assets/count_forgotten.pkl\" and \"assets/forgotten.pkl\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training 100 epochs. This may take some time.\n",
      "| Epoch [  1/100] Iter[  2]\t\tLoss: 3.6884 Acc@1: 9.766%%"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/envs/paddle2.0/lib/python3.7/site-packages/paddle/nn/layer/norm.py:636: UserWarning: When training, we now always track global mean and variance.\n",
      "  \"When training, we now always track global mean and variance.\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "| Epoch [ 72/100] Iter[316]\t\tLoss: 0.0000 Acc@1: 100.000%\r"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "| Epoch [ 93/100] Iter[348]\t\tLoss: 0.0000 Acc@1: 100.000%"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub message rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_msg_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "fe = it.ForgettingEventsInterpreter(model, True)\n",
    "\n",
    "epochs = 100\n",
    "print('Training %d epochs. This may take some time.' % epochs)\n",
    "stats, (count_forgotten, forgotten) = fe.interpret(\n",
    "    train_reader,\n",
    "    optimizer,\n",
    "    batch_size=BATCH_SIZE,\n",
    "    epochs=epochs,\n",
    "    save_path='assets')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the cell below, 9 most frequently forgotten samples and 9 never forgotten samples are visualized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['0 - airplance', '1 - automobile', '2 - bird', '3 - cat', '4 - deer', '5 - dog', '6 - frog', '7 - horse', '8 - ship', '9 - truck']\n",
      "The most frequently forgotten samples: \n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of never forgotten samples is 11997.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print([\n",
    "        '0 - airplance', '1 - automobile', '2 - bird', '3 - cat', '4 - deer',\n",
    "        '5 - dog', '6 - frog', '7 - horse', '8 - ship', '9 - truck'\n",
    "    ])\n",
    "\n",
    "max_count = max(count_forgotten.keys())\n",
    "max_count_n = len(count_forgotten[max_count])\n",
    "\n",
    "show_n = 9\n",
    "count = 0\n",
    "fig = plt.figure(figsize=(12, 12))\n",
    "axes = []\n",
    "print('The most frequently forgotten samples: ')\n",
    "for k in np.sort(np.array(list(count_forgotten.keys())))[::-1]:\n",
    "    for idx, i in enumerate(count_forgotten[k][:show_n - count]):\n",
    "        x = train_dataset[i][0].reshape((3, 32, 32)).transpose((1, 2, 0))\n",
    "        axes.append(fig.add_subplot(3, 3, idx + count + 1))\n",
    "        axes[-1].set_title(\n",
    "            'Forgotten {} times, \\n True label: {}, Learned as: {}'.format(\n",
    "                k, train_dataset[i][1], np.unique(forgotten[i])))\n",
    "        axes[-1].axis('off')\n",
    "        plt.imshow(x)\n",
    "    count += len(count_forgotten[k][:show_n - count])\n",
    "    if count >= show_n:\n",
    "        break\n",
    "plt.show()\n",
    "\n",
    "axes = []\n",
    "fig = plt.figure(figsize=(12, 12))\n",
    "zero_count_n = len(count_forgotten.get(0, []))\n",
    "print('Number of never forgotten samples is %d.' % (zero_count_n))\n",
    "for idx, i in enumerate(count_forgotten.get(0, [])[:show_n]):\n",
    "    x = train_dataset[i][0].reshape((3, 32, 32)).transpose((1, 2, 0))\n",
    "    axes.append(fig.add_subplot(3, 3, idx + 1))\n",
    "    axes[-1].set_title('label {}'.format(train_dataset[i][1]))\n",
    "    axes[-1].axis('off')\n",
    "    plt.imshow(x)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "firstEnv",
   "language": "python",
   "name": "firstenv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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